In this series of posts, we address types of fair lending discrimination that are commonly recognized by the regulatory and enforcement agencies. The points covered are risk areas that are often examined in the course of regulatory reviews. Today’s entry will cover the unfair practice known as “steering.” It is critical to bear in […]
Read More
After being at record lows for nearly a decade, the Fed has raised interest rates three times in the past fifteen months. Although the current rate of 1% is still historically low, the rate environment has been static up until December of 2016.
Read More
In an upcoming series of posts we address types of fair lending discrimination that are commonly recognized by the regulatory and enforcement agencies.
Read More
In our previous post, we addressed a few frequently encountered issues when using regression methods to conduct a fair lending analysis.
Read More
Evaluating loan application outcomes (approval or denial) in the context of fair lending is referred to as an “underwriting analysis.” Regression modeling is commonly employed in such analyses.
Read More
The FDIC recent released its Winter 2016 edition of Supervisory Insights. This edition was focused on credit risk trends.
Read More
In our previous post, we started introducing the concept of statistical significance. We began with making two important points. First, statistical methods are applied in order to estimate or measure an unknown. A sample of data is analyzed which is then used to draw conclusions about a larger population. This is known as statistical inference. […]
Read More
FDIC Chairman Gruenberg:“Revenue and net income were higher, loan balances grew, asset quality improved, and the number of unprofitable banks and ‘problem banks’ continued to fall,” Gruenberg said. “Community banks also reported solid results for the quarter and year with strong net income, revenue, and loan growth.
Read More
When statistical methods are applied to evaluate fair lending compliance, one of the metrics of interest is the statistical significance of measured differences in treatment of applicants. Such differences may be measured by such things as the interest rates charged on loans or the rates of denial for one group versus another (such as males […]
Read More
When conducting fair lending regression analysis of underwriting, we are examining a sample of loan applications that were either approved or denied. The practice is to regress denial (y=1 if denied, 0=approved) on a target group indicator variable and other attributes upon which the loan decision should have been based.
Read More